About the Opportunity
FADA is seeking a skilled Senior Geospatial Intelligence Analyst to contribute to the development of next-generation geospatial imagery and intelligence capabilities for defense, space, and national security missions. This hands-on role will serve as a key link between platform capabilities, user requirements, and mission needs. The candidate will support the integration of multi-source satellite data, user workflows, analytics modules, and external systems.
The ideal candidate combines domain expertise in GEOINT workflows, satellite imagery interpretation, geospatial platforms, along with strong full-stack development skills. They will contribute to the design and implementation of key geospatial capabilities, turning user needs into robust technical solutions that power real-world, mission-critical operations.
This is an unparalleled opportunity to contribute to a globally recognized leader in advanced technology, shaping the future of geospatial intelligence. The Geospatial Intelligence Analyst will report to the Director of Space Data Intelligence.
Key Responsibilities
- Develop and maintain robust full-stack geospatial software, encompassing interactive front-end components (map-based UIs, search/preview tools) and scalable back-end services (APIs for tasking, cataloging, data access).
- Build and maintain efficient geospatial data pipelines for ingesting, transforming, and indexing diverse imagery and metadata from multiple providers.
- Ensure seamless integration and interoperability with existing GIS systems, command-and-control platforms, and external data sources, including robust schema alignment (e.g., STAC, OGC, GeoJSON).
- Develop interactive, secure dashboards and reporting tools for advanced imagery visualization, change tracking, and report generation.
Conduct advanced spatial analysis, modeling, and interpretation of geospatial data to derive actionable intelligence for defense applications. - Develop and implement data quality checks, validation processes, and monitoring solutions to ensure data accuracy, consistency, and reliability.
- Actively participate in code reviews, version control, and CI/CD processes to ensure code quality, traceability, and system reliability.
- Develop clear documentation and user guides, providing expert technical support and training to end-users.
- Collaborate closely with solution architects, data scientists, and cross-functional teams to seamlessly integrate analytics and advanced AI modules into user workflows.
Qualifications & Experience
- Bachelor’s or Master’s degree in Geospatial Engineering, Remote Sensing, Computer Science, or a related technical field.
- 8+ years of experience in geospatial software development and space-based intelligence applications.
- Strong programming skills in Python and JavaScript, with experience building geospatial APIs, services, and interactive UIs.
- Experience with geospatial data processing tools and familiarity with imagery formats and metadata schemas.
- Familiarity with geospatial data standards (e.g., STAC, OGC), imagery formats, and geospatial databases.
Preferred Skills:
- Proficiency in Python, Java, or Node.js for full-stack geospatial software development, including building robust APIs, microservices, and interactive UIs.
- Strong experience with modern web frameworks (e.g., React, Angular, Vue.js) and geospatial mapping libraries for building compelling user interfaces.
- Strong proficiency in GIS software (e.g., ArcGIS) and principles of remote sensing.
- Hands-on experience with geospatial databases and data processing tools.
- Deep understanding of geospatial data types (EO/SAR imagery, vector data), formats (GeoJSON, GeoTIFF), and standards (OGC, STAC).
- Demonstrated ability to conduct advanced spatial analysis, modeling, and interpretation of complex geospatial data.
- Proven ability to build and maintain robust data pipelines for ingesting, transforming, and indexing large volumes of multi-source geospatial data.
- Experience with data quality control, governance, and metadata management for geospatial assets.
- Experience with ortho-rectification, atmospheric correction, DEMs, and georeferencing.
- Proficiency with containerization (Docker), orchestration (Kubernetes), and implementing CI/CD pipelines.
- Experience with cloud environments (e.g., AWS, Azure, GCP) for geospatial workloads.
- Familiarity with code review practices and version control systems.
- Experience supporting defense, intelligence, or space operations, with an understanding of relevant workflows (e.g., mission planning, ISR systems, command & control).
- Experience with satellite-based ISR, satellite tasking, and data fusion from multiple sensors.
- Exposure to AI/ML integration in geospatial applications, including expertise in AI applications for intelligence.
- Familiarity with cloud-based Earth Observation (EO) platforms (e.g., Google Earth Engine, SentinelHub, OpenEO).